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Sökning: WFRF:(Gruvberger Sofia)

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1.
  • Cirenajwis, Helena, et al. (författare)
  • Molecular stratification of metastatic melanoma using gene expression profiling: prediction of survival outcome and benefit from molecular targeted therapy.
  • 2015
  • Ingår i: Oncotarget. - Impact Journals, LLC. - 1949-2553. ; 6:14, s. 12297-12309
  • Tidskriftsartikel (refereegranskat)abstract
    • Melanoma is currently divided on a genetic level according to mutational status. However, this classification does not optimally predict prognosis. In prior studies, we have defined gene expression phenotypes (high-immune, pigmentation, proliferative and normal-like), which are predictive of survival outcome as well as informative of biology. Herein, we employed a population-based metastatic melanoma cohort and external cohorts to determine the prognostic and predictive significance of the gene expression phenotypes. We performed expression profiling on 214 cutaneous melanoma tumors and found an increased risk of developing distant metastases in the pigmentation (HR, 1.9; 95% CI, 1.05-3.28; P=0.03) and proliferative (HR, 2.8; 95% CI, 1.43-5.57; P=0.003) groups as compared to the high-immune response group. Further genetic characterization of melanomas using targeted deep-sequencing revealed similar mutational patterns across these phenotypes. We also used publicly available expression profiling data from melanoma patients treated with targeted or vaccine therapy in order to determine if our signatures predicted therapeutic response. In patients receiving targeted therapy, melanomas resistant to targeted therapy were enriched in the MITF-low proliferative subtype as compared to pre-treatment biopsies (P=0.02). In summary, the melanoma gene expression phenotypes are highly predictive of survival outcome and can further help to discriminate patients responding to targeted therapy.
2.
  • Kimbung, Siker, et al. (författare)
  • Co-targeting of the PI3K pathway improves the response of BRCA1 deficient breast cancer cells to PARP1 inhibition.
  • 2012
  • Ingår i: Cancer Letters. - Elsevier. - 1872-7980. ; 319:2, s. 232-241
  • Tidskriftsartikel (refereegranskat)abstract
    • Although pre-clinical and clinical studies on PARP1 inhibitors, alone and in combination with DNA-damaging agents, show promising results, further ways to improve and broaden the scope of application of this therapeutic approach are warranted. To this end, we have investigated the possibility of improving the response of BRCA1 mutant breast cancer cells to PARP1 inhibition by co-targeting the PI3K pathway. Human breast cancer cell lines with or without the expression of BRCA1 and/or PTEN were treated with PARP1 and PI3K inhibitors as single agents and in combination. PARP1 inhibition induced DNA damage conferring a G2/M arrest and decrease in viability, paralleled by the induction of apoptosis. PI3K inhibition alone caused a G1 arrest and decreased cell growth. Most importantly, sequential combination of PARP and PI3K inhibitors interacted synergistically to significantly decrease growth compared to PARP inhibition alone. Global transcriptional profiling revealed that this decrease in growth was associated with down-regulation of macromolecule biosynthesis and the induction of apoptosis. Taken together, these results suggest an improved treatment strategy for BRCA1-mutant and possibly also triple-negative breast cancers with similar molecular defects.
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4.
  • Bergenfelz, Caroline, et al. (författare)
  • Systemic Monocytic-MDSCs Are Generated from Monocytes and Correlate with Disease Progression in Breast Cancer Patients.
  • 2015
  • Ingår i: PLoS ONE. - Public Library of Science. - 1932-6203. ; 10:5
  • Tidskriftsartikel (refereegranskat)abstract
    • Myeloid-derived suppressor cells (MDSCs) are highly immunosuppressive myeloid cells, which increase in cancer patients. The molecular mechanism behind their generation and function is unclear. Whereas granulocytic-MDSCs correlate with poor overall survival in breast cancer, the presence and relevance of monocytic-MDSCs (Mo-MDSCs) is unknown. Here we report for the first time an enrichment of functional blood Mo-MDSCs in breast cancer patients before they acquire a typical Mo-MDSC surface phenotype. A clear population of Mo-MDSCs with the typical cell surface phenotype (CD14+HLA-DRlow/-CD86low/-CD80low/-CD163low/-) increased significantly first during disease progression and correlated to metastasis to lymph nodes and visceral organs. Furthermore, monocytes, comprising the Mo-MDSC population, from patients with metastatic breast cancer resemble the reprogrammed immunosuppressive monocytes in patients with severe infections, both by their surface and functional phenotype but also at their molecular gene expression profile. Our data suggest that monitoring the Mo-MDSC levels in breast cancer patients may represent a novel and simple biomarker for assessing disease progression.
5.
  • Gruvberger, Sofia (författare)
  • Estrogen receptor alpha and beta in breast cancer - gene expression profiles and clinical implications
  • 2005
  • Doktorsavhandling (övrigt vetenskapligt)abstract
    • Breast cancer is the most common malignancy in women in the Western world with about 10% of women developing breast cancer during their lifetime, of which one third will eventually succumb to the metastatic form of the disease. Breast cancer arises from the epithelial cells of the breast mammary gland, but the mechanisms involved in tumor initiation, progression, and metastasis are still not fully understood. However, estrogen and its receptors are believed to play a crucial role in these events. Estrogen receptor alpha (ERalpha) has long been identified as a target for treatment and numerous studies have shown that patients expressing ERalpha are more likely to respond to endocrine therapy such as tamoxifen; however a significant fraction become resistant. Little is known of the role of the second estrogen receptor, estrogen receptor beta (ERbeta), in breast tumor biology and therapy response. This thesis is primarily concerned with investigating the global differences in gene expression between tumors that express and do not express ERalpha and/or ERbeta, and the relationship of such profiles to outcome in the setting of tamoxifen therapy. The present study shows that ERalpha status in primary breast tumor biopsies is associated with a very distinct gene expression profile, as determined by cDNA microarrays, involving a large number of genes (Papers I and III). Only a small fraction of these ERalpha-associated genes have previously been identified as estrogen-responsive in cell culture (Paper I). In addition, not only is the ERalpha status as a binary variable encoded in the gene expression profiles, but also the actual level of protein content can be predicted, as well as the percent cells in the DNA synthesis phase of the cell cycle and other prognostic markers (Paper III). However, predicting response to tamoxifen using gene expression profiles from primary breast tumors was not possible in a cohort of 44 patient with varying ERalpha status and clinical outcome (Paper II). Additionally, a previously published prognosis predictor did not have any prognostic significance in this data, suggesting that different data sets and various tumor/patient/treatment characteristics selected influence the success of an array-based predictor for prognosis (Paper II). Much less is known about the transactivating properties of ERbeta and its relationship to ERalpha and tamoxifen response. Herein, the ERbeta protein is shown to have prognostic value after adjuvant tamoxifen therapy in a large patient set (n=353; Paper IV). However, subgroup analysis shows the effect to be only significant in patients with tumors lacking ERalpha. From cDNA microarray analysis of a subset of these tumors, an ERbeta-associated gene expression profile could be generated from the ERalpha negative group of tumors but not for the ERalpha positive group, further corroborating the notion that ERbeta selectively influences the biological processes in tumors lacking ERalpha (Paper IV). These results suggest that the small subset of ERalpha negative tumors responding to tamoxifen may be explained by the presence of ERbeta, and that ERbeta is not a surrogate marker for ERalpha but is associated with its own biological processes and may respond to tamoxifen via different target genes. In conclusion, together these studies have added to our understanding of the importance of estrogen receptor status and their biological consequences in breast cancer.
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6.
  • Gruvberger, Sofia, et al. (författare)
  • Estrogen receptor beta expression is associated with tamoxifen response in ER alpha-negative breast carcinoma
  • 2007
  • Ingår i: Clinical Cancer Research. - American Association for Cancer Research. - 1078-0432. ; 13:7, s. 1987-1994
  • Tidskriftsartikel (refereegranskat)abstract
    • PURPOSE: Endocrine therapies, such as tamoxifen, are commonly given to most patients with estrogen receptor (ERalpha)-positive breast carcinoma but are not indicated for persons with ERalpha-negative cancer. The factors responsible for response to tamoxifen in 5% to 10% of patients with ERalpha-negative tumors are not clear. The aim of the present study was to elucidate the biology and prognostic role of the second ER, ERbeta, in patients treated with adjuvant tamoxifen.EXPERIMENTAL DESIGN: We investigated ERbeta by immunohistochemistry in 353 stage II primary breast tumors from patients treated with 2 years adjuvant tamoxifen, and generated gene expression profiles for a representative subset of 88 tumors.RESULTS: ERbeta was associated with increased survival (distant disease-free survival, P = 0.01; overall survival, P = 0.22), and in particular within ERalpha-negative patients (P = 0.003; P = 0.04), but not in the ERalpha-positive subgroup (P = 0.49; P = 0.88). Lack of ERbeta conferred early relapse (hazard ratio, 14; 95% confidence interval, 1.8-106; P = 0.01) within the ERalpha-negative subgroup even after adjustment for other markers. ERalpha was an independent marker only within the ERbeta-negative tumors (hazard ratio, 0.44; 95% confidence interval, 0.21-0.89; P = 0.02). An ERbeta gene expression profile was identified and was markedly different from the ERalpha signature.CONCLUSION: Expression of ERbeta is an independent marker for favorable prognosis after adjuvant tamoxifen treatment in ERalpha-negative breast cancer patients and involves a gene expression program distinct from ERalpha. These results may be highly clinically significant, because in the United States alone, approximately 10,000 women are diagnosed annually with ERalpha-negative/ERbeta-positive breast carcinoma and may benefit from adjuvant tamoxifen.
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7.
  • Gruvberger, Sofia, et al. (författare)
  • Estrogen receptor status in breast cancer is associated with remarkably distinct gene expression patterns
  • 2001
  • Ingår i: Cancer Research. - American Association for Cancer Research Inc.. - 1538-7445. ; 61:16, s. 5979-5984
  • Tidskriftsartikel (refereegranskat)abstract
    • To investigate the phenotype associated with estrogen receptor alpha (ER) expression in breast carcinoma, gene expression profiles of 58 node-negative breast carcinomas discordant for ER status were determined using DNA microarray technology. Using artificial neural networks as well as standard hierarchical clustering techniques, the tumors could be classified according to ER status, and a list of genes which discriminate tumors according to ER status was generated. The artificial neural networks could accurately predict ER status even when excluding top discriminator genes, including ER itself. By reference to the serial analysis of gene expression database, we found that only a small proportion of the 100 most important ER discriminator genes were also regulated by estradiol in MCF-7 cells. The results provide evidence that ER+ and ER- tumors display remarkably different gene-expression phenotypes not solely explained by differences in estrogen responsiveness.
8.
  • Gruvberger, Sofia, et al. (författare)
  • Expression profiling to predict outcome in breast cancer: the influence of sample selection
  • 2003
  • Ingår i: Breast Cancer Research. - BioMed Central (BMC). - 1465-5411. ; 5:1, s. 23-26
  • Tidskriftsartikel (refereegranskat)abstract
    • Gene expression profiling of tumors using DNA microarrays is a promising method for predicting prognosis and treatment response in cancer patients. It was recently reported that expression profiles of sporadic breast cancers could be used to predict disease recurrence better than currently available clinical and histopathological prognostic factors. Having observed an overlap in those data between the genes that predict outcome and those that predict estrogen receptor- status, we examined their predictive power in an independent data set. We conclude that it may be important to define prognostic expression profiles separately for estrogen receptor--positive and estrogen receptor--negative tumors.
9.
10.
  • Gruvberger, Sofia, et al. (författare)
  • Microarrays in breast cancer research and clinical practice - the future lies ahead
  • 2006
  • Ingår i: Endocrine-Related Cancer. - Society for Endocrinology. - 1479-6821. ; 13:4, s. 1017-1031
  • Forskningsöversikt (refereegranskat)abstract
    • Molecular profiling for classification and prognostic purposes has demonstrated that the genetic signatures of tumors contain information regarding biological properties as well as clinical behavior. This review highlights the progress that has been made in the field of gene expression profiling of human breast cancer. Breast cancer has become one of the most intensely studied human malignancies in the genomic era; several hundred papers over the last few years have investigated various clinical and biological aspects of human breast cancer using high-throughput molecular profiling techniques. Given the grossly heterogeneous nature of the disease and the lack of robust conventional markers for disease prediction, prognosis, and response to treatment, the notion that a transcriptional profile comprising multiple genes, rather than any single gene or other parameter, will be more predictive of tumor behavior is both appealing and reasonable. Promising results have emerged from these studies, correlating gene expression profiles with prognosis, recurrence, metastatic potential, therapeutic response, as well as biological and functional aspects of the disease. Clearly, the integration of genomic approaches into the clinic lies in the near future, but prospective studies based on larger patient cohorts representing the whole spectrum of breast cancer, oncogenic pathway-based studies, attendant care in bioinformatic analyses and validation studies are needed before the full promise of gene expression profiling can be realized in the clinical setting.
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